Approaching parallel computing to simulating population dynamics in demography

Montanola Sales, Cristina and Onggo, Bhakti Satyabuhdi Stephan and Casanovas-Garcia, Josep and Cela-Espín, Jose María and Kaplan-Marcusán, Adriana (2016) Approaching parallel computing to simulating population dynamics in demography. Parallel Computing, 59. pp. 151-170. ISSN 0167-8191

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Abstract

Agent-based modelling and simulation is a promising methodology that can be applied in the study of population dynamics. The main advantage of this technique is that it allows representing the particularities of the individuals that are modeled along with the interactions that take place among them and their environment. Hence, classical numerical simulation approaches are less adequate for reproducing complex dynamics. Nowadays, there is a rise of interest on using distributed computing to perform large-scale simulation of social systems. However, the inherent complexity of this type of applications is challenging and requires the study of possible solutions from the parallel computing perspective (e.g., how to deal with fine grain or irregular workload). In this paper, we discuss the particularities of simulating populating dynamics by using parallel discrete event simulation methodologies. To illustrate our approach, we present a possible solution to make transparent the use of parallel simulation for modeling demographic systems: Yades tool. In Yades, modelers can easily define models that describe different demographic processes with a web user interface and transparently run them on any computer architecture environment thanks to its demographic simulation library and code generator. Therefore, transparency is provided by by two means: the provision of a web user interface where modelers and policy makers can specify their agent-based models with the tools they are familiar with, and the automatic generation of the simulation code that can be executed in any platform (cluster or supercomputer). A study is conducted to evaluate the performance of our solution in a High Performance Computing environment. The main benefit of this outline is that our findings can be generalized to problems with similar characteristics to our demographic simulation model.

Item Type:
Journal Article
Journal or Publication Title:
Parallel Computing
Additional Information:
This is the author’s version of a work that was accepted for publication in Parallel Computing. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Parallel Computing, 59, 2016 DOI: 10.1016/j.parco.2016.07.001
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/1700/1705
Subjects:
ID Code:
80488
Deposited By:
Deposited On:
21 Jul 2016 12:24
Refereed?:
Yes
Published?:
Published
Last Modified:
25 Sep 2020 02:40